Evolving neural network ensembles for control problems
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A cooperative constructive method for neural networks for pattern recognition
Pattern Recognition
Immune network based ensembles
Neurocomputing
Ensembling evidential k-nearest neighbor classifiers through multi-modal perturbation
Applied Soft Computing
Information Sciences: an International Journal
Nonlinear Boosting Projections for Ensemble Construction
The Journal of Machine Learning Research
Improving crossover operator for real-coded genetic algorithms using virtual parents
Journal of Heuristics
Particle swarm optimization based on dynamic niche technology with applications to conceptual design
Advances in Engineering Software
Heuristic speciation for evolving neural network ensemble
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Improving multiclass pattern recognition with a co-evolutionary RBFNN
Pattern Recognition Letters
Classifier ensemble selection using hybrid genetic algorithms
Pattern Recognition Letters
Increasing classification efficiency with multiple mirror classifiers
Expert Systems with Applications: An International Journal
Neural Network Ensembles for Classification Problems Using Multiobjective Genetic Algorithms
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
An Evolutionary Approach for Tuning Artificial Neural Network Parameters
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Boosting random subspace method
Neural Networks
Evolving an Ensemble of Neural Networks Using Artificial Immune Systems
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
A genetic encoding approach for learning methods for combining classifiers
Expert Systems with Applications: An International Journal
Evolvable neural networks ensembles for accidents diagnosis
ICCOMP'08 Proceedings of the 12th WSEAS international conference on Computers
Supervised projection approach for boosting classifiers
Pattern Recognition
Ensemble Learning: A Study on Different Variants of the Dynamic Selection Approach
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
CIXL2: a crossover operator for evolutionary algorithms based on population features
Journal of Artificial Intelligence Research
A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Group search optimizer: an optimization algorithm inspired by animal searching behavior
IEEE Transactions on Evolutionary Computation
A cooperative coevolution algorithm of RBFNN for classification
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Creating ensembles of classifiers via fuzzy clustering and deflection
Fuzzy Sets and Systems
Dual-population based coevolutionary algorithm for designing RBFNN with feature selection
Expert Systems with Applications: An International Journal
Evolutionary construction and adaptation of intelligent systems
Expert Systems with Applications: An International Journal
Genetic representation and evolvability of modular neural controllers
IEEE Computational Intelligence Magazine
Evolutionary FCMAC-BYY applied to stream data analysis
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
Municipal revenue prediction by ensembles of neural networks and support vector machines
WSEAS Transactions on Computers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Multiobjective optimization of ensembles of multilayer perceptrons for pattern classification
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Low voltage risk assessment in power system using neural network ensemble
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A group search optimizer for neural network training
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
A multi-objective neural network based method for cover crop identification from remote sensed data
Expert Systems with Applications: An International Journal
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Ensemble approaches for regression: A survey
ACM Computing Surveys (CSUR)
Evolving team behaviors with specialization
Genetic Programming and Evolvable Machines
Artificial neural network training using a new efficient optimization algorithm
Applied Soft Computing
Sustainable cooperative coevolution with a multi-armed bandit
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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This paper presents a cooperative coevolutive approach for designing neural network ensembles. Cooperative coevolution is a recent paradigm in evolutionary computation that allows the effective modeling of cooperative environments. Although theoretically, a single neural network with a sufficient number of neurons in the hidden layer would suffice to solve any problem, in practice many real-world problems are too hard to construct the appropriate network that solve them. In such problems, neural network ensembles are a successful alternative. Nevertheless, the design of neural network ensembles is a complex task. In this paper, we propose a general framework for designing neural network ensembles by means of cooperative coevolution. The proposed model has two main objectives: first, the improvement of the combination of the trained individual networks; second, the cooperative evolution of such networks, encouraging collaboration among them, instead of a separate training of each network. In order to favor the cooperation of the networks, each network is evaluated throughout the evolutionary process using a multiobjective method. For each network, different objectives are defined, considering not only its performance in the given problem, but also its cooperation with the rest of the networks. In addition, a population of ensembles is evolved, improving the combination of networks and obtaining subsets of networks to form ensembles that perform better than the combination of all the evolved networks. The proposed model is applied to ten real-world classification problems of a very different nature from the UCI machine learning repository and proben1 benchmark set. In all of them the performance of the model is better than the performance of standard ensembles in terms of generalization error. Moreover, the size of the obtained ensembles is also smaller.